@article{Nadakuditi2013WhenAT, title={When are the most informative components for inference also the principal components?}, author={Raj Rao Nadakuditi}, journal={CoRR}, year={2013}, volume={abs/1302.1232} }

- Published 2013 in ArXiv

Which components of the singular value decomposition of a signal-plus-noise data matrix are most informative for the inferential task of detecting or estimating an embedded low-rank signal matrix? Principal component analysis ascribes greater importance to the components that capture the greatest variation, i.e., the singular vectors associated with the… CONTINUE READING

### Presentations referencing similar topics